I. Field of the Invention
This disclosure relates generally to depth sensor systems, apparatus and methods, and more particularly to determining when to use a depth sensor in a mobile device and/or minimizing a bandwidth of an image send from a mobile device.
II. Background
Mobile phones and other mobile devices may include several sensors, such as one or more image sensors, image sensing devices, inertial sensors, magnetic compasses and a GNSS sensor. An image sensing device, such as an optical camera, may include one or more front and/or rear facing cameras. The inertial sensors may include an accelerometer and/or a gyroscope. The GNNS sensor may include a GPS receiver. Future mobile devices may also include a Kinect depth sensor and/or a structured light sensor. Advances in power optimization and miniaturization make mobile devices with such sensors more likely.
A Kinect depth sensor includes an infrared projector and a monochrome receiver, such as a CMOS (complimentary metal-oxide semiconductor) sensor, that work together. The infrared projector transmits a known pattern. The monochrome receiver receives a reflected infrared image that may be used to determine where objects are located and how far they are placed.
A structured light sensor transmits a predefined light pattern onto an object. Simultaneously, one or more image sensors observe the light patterns reflexed from nearby objects. The pattern reflected back varies as the distance between the mobile device and an object changes. Therefore, the pattern reflected back may also be used to determine where objects are located and how far they are placed.
Such sensors, which allow a mobile device to snapshot depths at any instant, require significant power to transmit a signal. This signal is then reflected and received back at the mobile device, which requires additional power. Furthermore, a large amount of bandwidth is occupied transmitting an image for cloud-based object detection. Additionally, search times are significant when receiving and searching through an image for an object as compared to a partial image. Moreover, privacy information may be revealed in an image. For example, background of an image may reveal a location of a person taking the image. What is needed is a way to improve object-detection and recognition times while using less bandwidth, image processing power and/or increasing privacy.